Abstract

Abstract There are developed methods for high-pressure turbine (HPT) blade loads and remaining useful life (RUL) prediction; however, they are ineffective and time-consuming for in-service HPT blades under actual operating conditions. Hence, it is necessary to use an acceptable computational effort to predict the HPT blade’s load and in-service lifetime. Drawing from the idea of the usage-based life (UBL) prediction method, this paper first proposes a framework for the life digital twin (LDT) to characterize and track the in-service life consumption of the HPT blades under actual operating conditions. The second work mainly focuses on developing the steady-state and transient load calculation surrogate models for the HPT blade’s LDT. Using the developed surrogate models, it can now calculate the steady-state and transient loads of the HPT blade in an acceptable time with the necessary accuracy. The proposed approach is demonstrated on an HPT blade of a typical commercial turbofan engine. Because the operating load of the HPT blade severely affects its in-service lifetime, the application of this approach enables the construction of an LDT of the HPT blade. It can reduce the uncertainty and variability associated with the in-service life prediction of the HPT blade under actual operating conditions.

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